Human–AI Co-Thinking Dynamics (HACD): Long-Term Effects of AI as a Thinking Space on Humans (Model v1.0, Status 2025)

The current debate on Artificial Intelligence focuses predominantly on system properties such as performance capability, training data, model architecture, safety, and regulation. Significantly less attention is given to the long-term effects that arise when humans do not use AI only situationally, but integrate it permanently as a space for thinking, writing, and reflection. This work addresses this research gap by presenting a theoretical impact model: Human–AI Co-Thinking Dynamics (HACD). The model does not describe properties of AI itself, but examines what happens within the human being when working over extended periods with linguistically coherent, permanently available, and low-friction systems. HACD is based on phenomenological observation, qualitative reflection, and temporal differentiation. It identifies universal impact phenomena, functional tipping points, human counter-movements, and protective factors that determine whether AI functions as a supportive thinking space or imperceptibly replaces processes of thinking and decision-making. The central finding is that AI does not generate depth, but amplifies existing human movements. Long-term effects are not determined by the system itself, but by human self-authorship, the ability to distinguish between form and truth, and the conscious handling of resonance and authority. This work is presented as a time-bound theoretical contribution (status 2025). It argues neither alarmistically nor euphorically, and provides a differentiated foundation for further empirical research and ethical reflection.